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| Section | Weight | Objectives |
|---|---|---|
| Introduction to OCI AI Services | 20% | - OCI AI Service APIs
|
| AI Foundations | 10% | - Artificial Intelligence basics and terminology
|
| Deep Learning Foundations | 15% | - Deep Learning and neural networks
|
| OCI AI Portfolio | 15% | - Overview of OCI AI offerings
|
| OCI Generative AI and Oracle 23ai | 10% | - OCI Generative AI Service features
|
| Machine Learning Foundations | 15% | - Machine Learning fundamentals
|
| Generative AI and Large Language Models | 15% | - Generative AI concepts
|
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NEW QUESTION # 17
Which feature is NOT supported as part of the OCI Language service ' s pretrained language processing capabilities?
Answer: A
Explanation:
The OCI Language service offers several pretrained language processing capabilities, including Text Classification, Sentiment Analysis, and Language Detection. However, it does not natively support Text Generation as a part of its core language processing capabilities. Text Generation typically involves creating new content based on input prompts, which is a feature more commonly associated with models specifically designed for natural language generation.
NEW QUESTION # 18
Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?
Answer: B
Explanation:
Natural Language Processing (NLP) is the AI domain associated with tasks such as identifying the sentiment of text and translating text between languages. NLP focuses on enabling machines to understand, interpret, and generate human language in a way that is both meaningful and useful. This domain covers a wide range of applications, including text classification, language translation, sentiment analysis, and more, all of which involve processing and analyzing natural language data.
NEW QUESTION # 19
What is " in-context learning " in the realm of Large Language Models (LLMs)?
Answer: A
Explanation:
" In-context learning " in the realm of Large Language Models (LLMs) refers to the ability of these models to learn and adapt to a specific task by being provided with a few examples of that task within the input prompt.
This approach allows the model to understand the desired pattern or structure from the given examples and apply it to generate the correct outputs for new, similar inputs. In-context learning is powerful because it does not require retraining the model; instead, it uses the examples provided within the context of the interaction to guide its behavior.
NEW QUESTION # 20
Which is NOT a capability of OCI Vision ' s image analysis?
Answer: D
Explanation:
OCI Vision ' s image analysis capabilities include locating and extracting text from images, assigning classification labels to images, and detecting objects with bounding boxes. However, translating text in images to another language is not a capability of OCI Vision ' s image analysis. This functionality typically requires an additional layer of processing, such as integration with a language translation service, which is beyond the scope of OCI Vision ' s core image analysis features.
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NEW QUESTION # 21
What is the primary purpose of reinforcement learning?
Answer: C
Explanation:
Reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by taking actions in an environment to achieve a certain goal. The agent receives feedback in the form of rewards or penalties based on the outcomes of its actions, which it uses to learn and improve its decision-making over time. The primary purpose of reinforcement learning is to enable the agent to learn optimal strategies by interacting with its environment, thereby maximizing cumulative rewards. This approach is commonly used in areas such as robotics, game playing, and autonomous systems.
NEW QUESTION # 22
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